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    MIMIC: An Innovative Methodology for Determining Mobile Laser Scanning System Point Density


    Cahalane, Conor and McElhinney, Conor P. and Lewis, Paul and McCarthy, Tim (2014) MIMIC: An Innovative Methodology for Determining Mobile Laser Scanning System Point Density. Remote Sensing, 6. pp. 7857-7877. ISSN 2072-4292

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    Abstract

    Understanding how various Mobile Mapping System (MMS) laser hardware configurations and operating parameters exercise different influence on point density is important for assessing system performance, which in turn facilitates system design and MMS benchmarking. Point density also influences data processing, as objects that can be recognised using automated algorithms generally require a minimum point density. Although obtaining the necessary point density impacts on hardware costs, survey time and data storage requirements, a method for accurately and rapidly assessing MMS performance is lacking for generic MMSs. We have developed a method for quantifying point clouds collected by an MMS with respect to known objects at specified distances using 3D surface normals, 2D geometric formulae and line drawing algorithms. These algorithms were combined in a system called the Mobile Mapping Point Density Calculator (MIMIC) and were validated using point clouds captured by both a single scanner and a dual scanner MMS. Results from MIMIC were promising: when considering the number of scan profiles striking the target, the average error equated to less than 1 point per scan profile. These tests highlight that MIMIC is capable of accurately calculating point density for both single and dual scanner MMSs.

    Item Type: Article
    Additional Information: © 2014 by the authors; licensee MDPI, Basel, Switzerland This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/).
    Keywords: point density; mobile mapping systems; performance; LiDAR;
    Academic Unit: Faculty of Science and Engineering > Research Institutes > National Centre for Geocomputation, NCG
    Item ID: 6938
    Identification Number: https://doi.org/10.3390/rs6097857
    Depositing User: Conor Cahalane
    Date Deposited: 01 Feb 2016 15:32
    Journal or Publication Title: Remote Sensing
    Publisher: MDPI
    Refereed: Yes
    Funders: Irish Research Council (IRC), Pavement Management Services Ltd, National Roads Authority (ERA-NET SR01 projects), Science Foundation Ireland (SFI)
    URI:

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